Correlation Between Vine Hill and M3 Brigade
Can any of the company-specific risk be diversified away by investing in both Vine Hill and M3 Brigade at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Vine Hill and M3 Brigade into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Vine Hill Capital and M3 Brigade Acquisition V, you can compare the effects of market volatilities on Vine Hill and M3 Brigade and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Vine Hill with a short position of M3 Brigade. Check out your portfolio center. Please also check ongoing floating volatility patterns of Vine Hill and M3 Brigade.
Diversification Opportunities for Vine Hill and M3 Brigade
-0.05 | Correlation Coefficient |
Good diversification
The 3 months correlation between Vine and MBAV is -0.05. Overlapping area represents the amount of risk that can be diversified away by holding Vine Hill Capital and M3 Brigade Acquisition V in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on M3 Brigade Acquisition and Vine Hill is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Vine Hill Capital are associated (or correlated) with M3 Brigade. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of M3 Brigade Acquisition has no effect on the direction of Vine Hill i.e., Vine Hill and M3 Brigade go up and down completely randomly.
Pair Corralation between Vine Hill and M3 Brigade
Given the investment horizon of 90 days Vine Hill is expected to generate 1.9 times less return on investment than M3 Brigade. In addition to that, Vine Hill is 1.13 times more volatile than M3 Brigade Acquisition V. It trades about 0.08 of its total potential returns per unit of risk. M3 Brigade Acquisition V is currently generating about 0.17 per unit of volatility. If you would invest 1,003 in M3 Brigade Acquisition V on September 12, 2024 and sell it today you would earn a total of 2.00 from holding M3 Brigade Acquisition V or generate 0.2% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 95.45% |
| Values | Daily Returns |
Vine Hill Capital vs. M3 Brigade Acquisition V
Performance |
| Timeline |
| Vine Hill Capital |
| M3 Brigade Acquisition |
Vine Hill and M3 Brigade Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Vine Hill and M3 Brigade
The main advantage of trading using opposite Vine Hill and M3 Brigade positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Vine Hill position performs unexpectedly, M3 Brigade can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in M3 Brigade will offset losses from the drop in M3 Brigade's long position.| Vine Hill vs. Distoken Acquisition | Vine Hill vs. dMY Squared Technology | Vine Hill vs. YHN Acquisition I | Vine Hill vs. CO2 Energy Transition |
| M3 Brigade vs. Distoken Acquisition | M3 Brigade vs. dMY Squared Technology | M3 Brigade vs. YHN Acquisition I | M3 Brigade vs. CO2 Energy Transition |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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